NLTK Named Entity recognition to a Python list

Question

I used NLTK\'s ne_chunk to extract named entities from a text:

my_sent = \"WASHINGTON -- In the wake of a string of abuses by New York police of         


        

Answer 1

You can also extract the label of each Name Entity in the text using this code:

import nltk
for sent in nltk.sent_tokenize(sentence):
   for chunk in nltk.ne_chunk(nltk.pos_tag(nltk.word_tokenize(sent))):
      if hasattr(chunk, 'label'):
         print(chunk.label(), ' '.join(c[0] for c in chunk))

Output:

GPE WASHINGTON
GPE New York
PERSON Loretta E. Lynch
GPE Brooklyn

You can see Washington, New York and Brooklyn are GPE means geo-political entities

and Loretta E. Lynch is a PERSON